Matthew L. Daggitt

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 30

Top Topics

Tableau Calculus

Language Understanding

Top Venues

Comput. Geosci.

Publications

Matthew L. Daggitt, Wen Kokke, Robert Atkey, Natalia Slusarz, Luca Arnaboldi, Ekaterina Komendantskaya
Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs. CoRR (2024)
Matthew L. Daggitt, Timothy G. Griffin
Formally Verified Convergence of Policy-Rich DBF Routing Protocols. IEEE/ACM Trans. Netw. 32 (2) (2024)
Matthew L. Daggitt, Wen Kokke, Robert Atkey
Efficient compilation of expressive problem space specifications to neural network solvers. CoRR (2024)
Haoze Wu, Omri Isac, Aleksandar Zeljic, Teruhiro Tagomori, Matthew L. Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, Clark W. Barrett
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. CAV (2) (2024)
Marco Casadio, Tanvi Dinkar, Ekaterina Komendantskaya, Luca Arnaboldi, Omri Isac, Matthew L. Daggitt, Guy Katz, Verena Rieser, Oliver Lemon
NLP Verification: Towards a General Methodology for Certifying Robustness. CoRR (2024)
Haoze Wu, Omri Isac, Aleksandar Zeljic, Teruhiro Tagomori, Matthew L. Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, Clark W. Barrett
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. CoRR (2024)
Matthew L. Daggitt, Wen Kokke, Ekaterina Komendantskaya, Robert Atkey, Luca Arnaboldi, Natalia Slusarz, Marco Casadio, Ben Coke, Jeonghyeon Lee
The Vehicle Tutorial: Neural Network Verification with Vehicle. FoMLAS@CAV (2023)
Marco Casadio, Luca Arnaboldi, Matthew L. Daggitt, Omri Isac, Tanvi Dinkar, Daniel Kienitz, Verena Rieser, Ekaterina Komendantskaya
ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verification. FoMLAS@CAV (2023)
Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart, Kathrin Stark
Logic of Differentiable Logics: Towards a Uniform Semantics of DL. LPAR (2023)
Matthew L. Daggitt, Robert Atkey, Wen Kokke, Ekaterina Komendantskaya, Luca Arnaboldi
Compiling Higher-Order Specifications to SMT Solvers: How to Deal with Rejection Constructively. CPP (2023)
Marco Casadio, Luca Arnaboldi, Matthew L. Daggitt, Omri Isac, Tanvi Dinkar, Daniel Kienitz, Verena Rieser, Ekaterina Komendantskaya
ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verification. CoRR (2023)
Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart, Kathrin Stark
Logic of Differentiable Logics: Towards a Uniform Semantics of DL. CoRR (2023)
Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart
Differentiable Logics for Neural Network Training and Verification. CoRR (2022)
Matthew L. Daggitt, Timothy G. Griffin
Dynamic asynchronous iterations. J. Parallel Distributed Comput. 164 (2022)
Marco Casadio, Ekaterina Komendantskaya, Matthew L. Daggitt, Wen Kokke, Guy Katz, Guy Amir, Idan Refaeli
Neural Network Robustness as a Verification Property: A Principled Case Study. CAV (1) (2022)
Ruby C. Marsden, Christopher L. Kirkland, Martin Danisík, Matthew L. Daggitt, Ung-San Ahn, Bjarne Friedrichs, Noreen J. Evans
A new approach to SHRIMP II zircon U-Th disequilibrium dating. Comput. Geosci. 158 (2022)
Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart
Differentiable Logics for Neural Network Training and Verification. NSV/FoMLAS@CAV (2022)
T. Scharf, Christopher L. Kirkland, Matthew L. Daggitt, Milo Barham, Vladimir Puzyrev
AnalyZr: A Python application for zircon grain image segmentation and shape analysis. Comput. Geosci. 162 (2022)
Matthew L. Daggitt, Wen Kokke, Robert Atkey, Luca Arnaboldi, Ekaterina Komendantskaya
Vehicle: Interfacing Neural Network Verifiers with Interactive Theorem Provers. CoRR (2022)
Marco Casadio, Ekaterina Komendantskaya, Verena Rieser, Matthew L. Daggitt, Daniel Kienitz, Luca Arnaboldi, Wen Kokke
Why Robust Natural Language Understanding is a Challenge. CoRR (2022)
Remi Desmartin, Grant O. Passmore, Ekaterina Komendantskaya, Matthew L. Daggitt
CheckINN: Wide Range Neural Network Verification in Imandra (Extended). CoRR (2022)
Matthew L. Daggitt, Timothy G. Griffin
Formally Verified Convergence of Policy-Rich DBF Routing Protocols. CoRR (2021)
Marco Casadio, Matthew L. Daggitt, Ekaterina Komendantskaya, Wen Kokke, Daniel Kienitz, Rob Stewart
Property-driven Training: All You (N)Ever Wanted to Know About. CoRR (2021)
Alasdair Hill, Ekaterina Komendantskaya, Matthew L. Daggitt, Ronald P. A. Petrick
Actions you can handle: dependent types for AI plans. TyDe@ICFP (2021)
Alasdair Hill, Ekaterina Komendantskaya, Matthew L. Daggitt, Ronald P. A. Petrick
Actions You Can Handle: Dependent Types for AI Plans. CoRR (2021)
Matthew L. Daggitt, Ran Zmigrod, Timothy G. Griffin
A Relaxation of Üresin and Dubois' Asynchronous Fixed-Point Theory in Agda. J. Autom. Reason. 64 (5) (2020)
Matthew L. Daggitt, Timothy G. Griffin
Dynamic Asynchronous Iterations. CoRR (2020)
Ran Zmigrod, Matthew L. Daggitt, Timothy G. Griffin
An Agda Formalization of Üresin and Dubois' Asynchronous Fixed-Point Theory. ITP (2018)
Matthew L. Daggitt, Alexander J. T. Gurney, Timothy G. Griffin
Asynchronous convergence of policy-rich distributed bellman-ford routing protocols. SIGCOMM (2018)
Matthew L. Daggitt, Timothy G. Griffin
Rate of Convergence of Increasing Path-Vector Routing Protocols. ICNP (2018)